Finding Ideal Parameters for Recycled Material Fused Particle Fabrication-Based 3D Printing Using an Open Source Software Implementation of Particle Swarm Optimization

As additive manufacturing rapidly expands the number of materials including waste plastics and composites, there is an urgent need to reduce the experimental time needed to identify optimized printing parameters for novel materials. Computational intelligence (CI) in general and particle swarm optimization (PSO) algorithms in particular have been shown to accelerate finding optimal printing parameters. Unfortunately, the implementation of CI has been prohibitively complex for noncomputer scientists. To overcome these limitations, this article develops, tests, and validates PSO Experimenter, an easy-to-use open-source platform based around the PSO algorithm and applies it to optimizing recycled materials. Specifically, PSO Experimenter is used to find optimal printing parameters for a relatively unexplored potential distributed recycling and additive manufacturing (DRAM) material that is widely available: low-density polyethylene (LDPE). LDPE has been used to make filament, but in this study for the first time it was used in the open source fused particle fabrication/fused granular fabrication system. PSO Experimenter successfully identified functional printing parameters for this challenging-to-print waste plastic. The results indicate that PSO Experimenter can provide 97% reduction in research time for 3D printing parameter optimization. It is concluded that the PSO Experimenter is a user-friendly and effective free software for finding ideal parameters for the burgeoning challenge of DRAM as well as a wide range of other fields and processes

Predictors of Occurrence and Severity of First Time Low Back Pain Episodes: Findings from a Military Inception Cohort

Primary prevention studies suggest that additional research on identifying risk factors predictive of low back pain (LBP) is necessary before additional interventions can be developed. In the current study we assembled a large military cohort that was initially free of LBP and followed over 2 years. The purposes of this study were to identify baseline variables from demographic, socioeconomic, general health, and psychological domains that were predictive of a) occurrence; b) time; and c) severity for first episode of self-reported LBP. Baseline and outcome measures were collected via web-based surveillance system or phone to capture monthly information over 2 years. The assembled cohort consisted of 1230 Soldiers who provided self-report data with 518 (42.1%) reporting at least one episode of LBP over 2 years. Multivariate logistic regression analysis indicated that gender, active duty status, mental and physical health scores were significant predictors of LBP. Cox regression revealed that the time to first episode of LBP was significantly shorter for Soldiers that were female, active duty, reported previous injury, and had increased BMI. Multivariate linear regression analysis investigated severity of the first episode by identifying baseline predictors of pain intensity, disability, and psychological distress. Education level and physical fitness were consistent predictors of pain intensity, while gender, smoking status, and previous injury status were predictors of disability. Gender, smoking status, physical health scores, and beliefs of back pain were consistent predictors of psychological distress. These results provide additional data to confirm the multi-factorial nature of LBP and suggest future preventative interventions focus on multi-modal approaches that target modifiable risk factors specific to the population of interest

Open source framework for a Broadly Expandable and Reconfigurable data acquisition and automation device (BREAD)

Though open source data acquisition (DAQ) systems have been published, closed source proprietary systems are the standard despite often being prohibitively expensive. High costs, however, limit access to high-quality DAQ in low-resource settings. In many cases the functions executed by the closed source and proprietary DAQ cards could be carried out by an open source alternative; however, as desired function count increases, the simplicity of integrating the designs decreases substantially. Although the global library of open source electronic designs is expanding rapidly, and there is clear evidence they can reduce costs for scientists one device at a time, they are generally made to carry a function well, but are often not capable of scaling up or easily being integrated with other designs. Just as other open source projects have found success by having modular frameworks and clearly documented specifications, a framework to unify and enable interoperation of these open source electronics systems would be greatly beneficial to the scientific community. To meet these needs and ensure greater accessibility to high-quality electronics sensing and DAQ systems, this article shares and tests a news framework where new open source electronics can be developed and have plug-and-play functionality. The Broadly Reconfigurable and Expandable Automation Device (BREAD), consists of a basic set of guidelines and requirements to which others can contribute. Here 7 slices (boards) are provided, demonstrated, and validated: 1) Amplified Analog Input, 2) Audio Analysis / Fourier Transform, 3) +/- 10A Current Sensor, 4) 4-Channel Relay Controller 5) 4 Channel Stepper Motor Controller, 6) 4 Channel Type-K Thermocouple Reader and 7) 2 Channel USB Port. Implementing systems using BREAD rather than closed source and proprietary alternatives can result in cost savings of up to 93%

Short and long-term effectiveness of couple counselling: a study protocol

<p>Abstract</p> <p>Background</p> <p>Healthy couple relationships are fundamental to a healthy society, whereas relationship breakdown and discord are linked to a wide range of negative health and wellbeing outcomes. Two types of relationship services (couple counselling and relationship education) have demonstrated efficacy in many controlled studies but evidence of the effectiveness of community-based relationship services has lagged behind. This study protocol describes an effectiveness evaluation of the two types of community-based relationship services. The aims of the Evaluation of Couple Counselling study are to: map the profiles of clients seeking agency-based couple counselling and relationship enhancement programs in terms of socio-demographic, relationship, health, and health service use indicators; to determine 3 and 12-month outcomes for relationship satisfaction, commitment, and depression; and determine relative contributions of client and therapy factors to outcomes.</p> <p>Methods/Design</p> <p>A quasi-experimental pre-post-post evaluation design is used to assess outcomes for couples presenting for the two types of community-based relationship services. The longitudinal design involves a pre-treatment survey and two follow-up surveys at 3- and 12-months post-intervention. The study is set in eight Relationships Australia Victoria centres, across metropolitan, outer suburbs, and regional/rural sites. Relationships Australia, a non-government organisation, is the largest provider of couple counselling and relationship services in Australia. The key outcomes are couple satisfaction, relationship commitment, and depression measured by the CESD-10. Multi-level modelling will be used to account for the dyadic nature of couple data.</p> <p>Discussion</p> <p>The study protocol describes the first large scale investigation of the effectiveness of two types of relationship services to be conducted in Australia. Its significance lies in providing more detailed profiles of couples who seek relationship services, in evaluating both 3 and 12-month relationship and health outcomes, and in determining factors that best predict improvements. It builds on prior research by using a naturalistic sample, an effectiveness research design, a more robust measure of relationship satisfaction, robust health indicators, a 12-month follow-up period, and a more rigorous statistical procedure suitable for dyadic data. Findings will provide a more precise description of those seeking relationship services and factors associated with improved relationship and health outcomes.</p